On June 22nd from 14:00-15:30 CET, digital culture theorist Lev Manovich will give an online talk entitled, “What Does Data Want? Can We Think Without Categories? Can Computer Vision Help Us Understand Art?”
In the last fifteen years, many researchers started to apply AI and data science methods to the analysis of large cultural datasets. This research generated many interesting results, leading to hundreds of thousands of conference papers and journal articles, and development of new research areas and paradigms (a big part of digital humanities, cultural analytics, culturomics, etc.)
But is it possible that we remain blind to the fundamental differences between cultural data and other kinds of data? Why do we approach cultural and social data today using ideas developed in the 18th and 19th century, before digital computers and big data? How do aesthetic experiences made possible by millions of Instagram images by non-professional creators challenge computer vision?
These are the questions that Manovich will address in his talk, which will be presented by the Visual Narrative research group of the Lucerne University of Applied Arts and Sciences. The talk is organized by Katrina Sluis and Wolfgang Brückle, head of the research project Postphotography.
About Lev Manovich
Lev Manovich is one of the leading theorists of digital culture worldwide, and a pioneer in the application of data science for analysis of contemporary culture. Manovich is the author and editor of 13 books including AI Aesthetics, Theories of Software Culture, Instagram and Contemporary Image, Software Takes Command, Soft Cinema: Navigating the Database and The Language of New Media which was described as “the most suggestive and broad-ranging media history since Marshall McLuhan.” He was included in the list of “25 People Shaping the Future of Design” in 2013 and the list of “50 Most Interesting People Building the Future” in 2014. Manovich is a Presidential Professor at The Graduate Center, CUNY, and a Director of the Cultural Analytics Lab that pioneered analysis of visual culture using computational methods.
Source: Lucerne University of Applied Arts and Sciences
